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DSM辅助下城区大比例尺正射影像镶嵌线智能检测

左志权   

  1. 武汉大学遥感信息工程学院
  • 收稿日期:2010-05-17 修回日期:2010-07-12 出版日期:2011-02-25 发布日期:2011-02-25
  • 通讯作者: 左志权

Seamlines Intelligent Detection in Large-scale Urban Orthoimage Mosaicking

  • Received:2010-05-17 Revised:2010-07-12 Online:2011-02-25 Published:2011-02-25

摘要: 传统算法以重叠区域色彩(或灰度)差值图像为正射影像镶嵌线检测基础,可以很好地避开色差区域,但对建筑物高密集的城区效果不明显。本文以高精度数字表面模型为检测基础,通过智能识别处理手段对地面区域与非地面区域进行良好区分。传统镶嵌线检测算法都是以迭代运算为基础的智能算法,算法复杂度高。本文发展出一种贪婪蛇型算法,该算法仅与搜索步距、方向旋转间隔、以及重叠区域宽度等三个因素相关,具有速度快,效率高等优点。针对典型的城市区域进行镶嵌线检测实验,结果表明DSM辅助下的城区正射影像镶嵌线能很好地避开房屋等明显地表实体,并且贪婪蛇型算法能有效地进行最优路径检测。

Abstract: Traditional algorithm can avoid color difference areas effectively by using seamlines detection in overlapping color difference image.. However, high density of urban buildings using this method is not good. In this paper, we distinguish ground regional and non-ground area accurately by processing high-precision DSM. Most of traditional seamlines detection algorithms are based on iterative calculations, and have high complexity. Our paper propose a new algorithm named greedy snake algorithm. The new algorithm is only associated with three parameters: searching step, direction rotation interval and region width. We carried out experiments for urban areas for orthophoto seamlines detection. The results show that the seamlines can avoid buildings well, and the greedy snake algorithm can be applied in the optimal path detection effectively.